Literature DB >> 27239323

Can meta-omics help to establish causality between contaminant biotransformations and genes or gene products?

David R Johnson1, Damian E Helbling2, Yujie Men3, Kathrin Fenner4.   

Abstract

There is increasing interest in using meta-omics association studies to investigate contaminant biotransformations. The general strategy is to characterize the complete set of genes, transcripts, or enzymes from in situ environmental communities and use the abundances of particular genes, transcripts, or enzymes to establish associations with the communities' potential to biotransform one or more contaminants. The associations can then be used to generate hypotheses about the underlying biological causes of particular biotransformations. While meta-omics association studies are undoubtedly powerful, they have a tendency to generate large numbers of non-causal associations, making it potentially difficult to identify the genes, transcripts, or enzymes that cause or promote a particular biotransformation. In this perspective, we describe general scenarios that could lead to pervasive non-causal associations or conceal causal associations. We next explore our own published data for evidence of pervasive non-causal associations. Finally, we evaluate whether causal associations could be identified despite the discussed limitations. Analysis of our own published data suggests that, despite their limitations, meta-omics association studies might still be useful for improving our understanding and predicting the contaminant biotransformation capacities of microbial communities.

Entities:  

Year:  2015        PMID: 27239323      PMCID: PMC4880034          DOI: 10.1039/C5EW00016E

Source DB:  PubMed          Journal:  Environ Sci (Camb)        ISSN: 2053-1400            Impact factor:   4.251


  34 in total

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5.  Sustainable syntrophic growth of Dehalococcoides ethenogenes strain 195 with Desulfovibrio vulgaris Hildenborough and Methanobacterium congolense: global transcriptomic and proteomic analyses.

Authors:  Yujie Men; Helene Feil; Nathan C Verberkmoes; Manesh B Shah; David R Johnson; Patrick K H Lee; Kimberlee A West; Stephen H Zinder; Gary L Andersen; Lisa Alvarez-Cohen
Journal:  ISME J       Date:  2011-09-01       Impact factor: 10.302

6.  A framework for establishing predictive relationships between specific bacterial 16S rRNA sequence abundances and biotransformation rates.

Authors:  Damian E Helbling; David R Johnson; Tae Kwon Lee; Andreas Scheidegger; Kathrin Fenner
Journal:  Water Res       Date:  2014-12-16       Impact factor: 11.236

7.  Tuning the performance of a natural treatment process using metagenomics for improved trace organic chemical attenuation.

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Review 8.  Emerging chemicals and the evolution of biodegradation capacities and pathways in bacteria.

Authors:  Boris A Kolvenbach; Damian E Helbling; Hans-Peter E Kohler; Philippe F-X Corvini
Journal:  Curr Opin Biotechnol       Date:  2013-09-17       Impact factor: 9.740

9.  Biodegradation of methyl tert-butyl ether by a pure bacterial culture.

Authors:  P B Hatzinger; K McClay; S Vainberg; M Tugusheva; C W Condee; R J Steffan
Journal:  Appl Environ Microbiol       Date:  2001-12       Impact factor: 4.792

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Journal:  Nature       Date:  2013-07-28       Impact factor: 49.962

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2.  Micropollutant degradation via extracted native enzymes from activated sludge.

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Journal:  Water Res       Date:  2016-03-15       Impact factor: 11.236

Review 3.  Extremophilic Microfactories: Applications in Metal and Radionuclide Bioremediation.

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Journal:  Front Microbiol       Date:  2018-06-01       Impact factor: 5.640

Review 4.  Methodological Advances to Study Contaminant Biotransformation: New Prospects for Understanding and Reducing Environmental Persistence?

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Journal:  ACS ES T Water       Date:  2021-06-24

Review 5.  Bacterial Biosorbents, an Efficient Heavy Metals Green Clean-Up Strategy: Prospects, Challenges, and Opportunities.

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